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A two-stage hierarchical regression model for meta-analysis of epidemiologic nonlinear dose-response data

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  • Liu, Qin
  • Cook, Nancy R.
  • Bergström, Anna
  • Hsieh, Chung-Cheng

Abstract

To estimate a summarized dose-response relation across different exposure levels from epidemiologic data, meta-analysis often needs to take into account heterogeneity across studies beyond the variation associated with fixed effects. We extended a generalized-least-squares method and a multivariate maximum likelihood method to estimate the summarized nonlinear dose-response relation taking into account random effects. These methods are readily suited to fitting and testing models with covariates and curvilinear dose-response relations.

Suggested Citation

  • Liu, Qin & Cook, Nancy R. & Bergström, Anna & Hsieh, Chung-Cheng, 2009. "A two-stage hierarchical regression model for meta-analysis of epidemiologic nonlinear dose-response data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4157-4167, October.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:4157-4167
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    References listed on IDEAS

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    1. Nicola Orsini & Rino Bellocco & Sander Greenland, 2006. "Generalized least squares for trend estimation of summarized dose–response data," Stata Journal, StataCorp LP, vol. 6(1), pages 40-57, March.
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    2. Crippa, Alessio & Orsini, Nicola, 2016. "Multivariate Dose-Response Meta-Analysis: The dosresmeta R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(c01).
    3. Lingqian Xu & Debapriya Mondal & David A. Polya, 2020. "Positive Association of Cardiovascular Disease (CVD) with Chronic Exposure to Drinking Water Arsenic (As) at Concentrations below the WHO Provisional Guideline Value: A Systematic Review and Meta-anal," IJERPH, MDPI, vol. 17(7), pages 1-24, April.
    4. Bo Yang & Feng-Lei Wang & Xiao-Li Ren & Duo Li, 2014. "Biospecimen Long-Chain N-3 PUFA and Risk of Colorectal Cancer: A Meta-Analysis of Data from 60,627 Individuals," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-13, November.

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